Crowd V-IoE: Visual Internet of Everything Architecture in AI-Driven Fog Computing

Fog computing has emerged as a unifying platform to provide computing, communication, and storage for a variety of mobile applications. That helps achieve high bandwidth, high intelligence, low latency, and low energy consumption in handling massive networking devices and emerging rich multimedia se...

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Veröffentlicht in:IEEE wireless communications 2020-04, Vol.27 (2), p.51-57
Hauptverfasser: Ji, Wen, Liang, Bing, Wang, Yuqin, Qiu, Rui, Yang, Zheming
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container_end_page 57
container_issue 2
container_start_page 51
container_title IEEE wireless communications
container_volume 27
creator Ji, Wen
Liang, Bing
Wang, Yuqin
Qiu, Rui
Yang, Zheming
description Fog computing has emerged as a unifying platform to provide computing, communication, and storage for a variety of mobile applications. That helps achieve high bandwidth, high intelligence, low latency, and low energy consumption in handling massive networking devices and emerging rich multimedia services in 5G networks. Current prominence and future promises are changing from the Internet of Things (IoT) to the Internet of Everything (IoE), which is a union of people, process, data, and things. However, the development of fog radio access networks (F-RANs) is challenged by the diversity of IoE, ultra-high-definition videos on demand from users, and low-latency requirement of heterogeneous IoT devices. In this article, we present an architecture of visual IoE (V-IoE) in F-RANs. We systemically analyze the key challenges of V-IoE from the perspective of F-RANs, and propose a crowd V-IoE architecture. Through experimental results, we demonstrate that our proposed architecture exhibits better performance with lower bandwidth requirement, lower energy consumption, and lower latency in F-RANs. Finally, we conclude with a discussion of potential directions.
doi_str_mv 10.1109/MWC.001.1900349
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subjects Applications programs
Artificial intelligence
Bandwidths
Cloud computing
Computer architecture
Computer Science
Computer Science, Hardware & Architecture
Computer Science, Information Systems
Crowdsourcing
Edge computing
Electronic devices
Energy consumption
Engineering
Engineering, Electrical & Electronic
High definition
Internet of Things
Mobile computing
Multimedia
Network latency
Science & Technology
Streaming media
Technology
Telecommunications
Videos
Wireless networks
title Crowd V-IoE: Visual Internet of Everything Architecture in AI-Driven Fog Computing
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